Find, fix and prevent vulnerabilities in your code.
high severity
- Vulnerable module: kerberos
- Introduced through: kerberos@0.0.22
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › kerberos@0.0.22Remediation: Upgrade to kerberos@1.0.0.
Overview
Affected versions of this package are vulnerable to DLL Injection. An attacker can execute arbitrary code by creating a file with the same name in a folder that precedes the intended file in the DLL path search.
Remediation
Upgrade kerberos
to version 1.0.0 or higher.
References
high severity
- Vulnerable module: bson
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › bson@1.0.9Remediation: Upgrade to mongoose@5.3.9.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › mongodb@2.2.34 › mongodb-core@2.1.18 › bson@1.0.9Remediation: Upgrade to mongoose@5.2.9.
Overview
bson is a BSON Parser for node and browser.
Affected versions of this package are vulnerable to Internal Property Tampering. The package will ignore an unknown value for an object's _bsotype
, leading to cases where an object is serialized as a document rather than the intended BSON type.
NOTE: This vulnerability has also been identified as: CVE-2019-2391
Remediation
Upgrade bson
to version 1.1.4 or higher.
References
high severity
- Vulnerable module: bson
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › bson@1.0.9Remediation: Upgrade to mongoose@5.3.9.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › mongodb@2.2.34 › mongodb-core@2.1.18 › bson@1.0.9Remediation: Upgrade to mongoose@5.2.9.
Overview
bson is a BSON Parser for node and browser.
Affected versions of this package are vulnerable to Internal Property Tampering. The package will ignore an unknown value for an object's _bsotype
, leading to cases where an object is serialized as a document rather than the intended BSON type.
NOTE: This vulnerability has also been identified as: CVE-2020-7610
Remediation
Upgrade bson
to version 1.1.4 or higher.
References
high severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21Remediation: Upgrade to mongoose@5.13.20.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Prototype Pollution in document.js
, via update functions such as findByIdAndUpdate()
. This allows attackers to achieve remote code execution.
Note: Only applications using Express and EJS are vulnerable.
PoC
import { connect, model, Schema } from 'mongoose';
await connect('mongodb://127.0.0.1:27017/exploit');
const Example = model('Example', new Schema({ hello: String }));
const example = await new Example({ hello: 'world!' }).save();
await Example.findByIdAndUpdate(example._id, {
$rename: {
hello: '__proto__.polluted'
}
});
// this is what causes the pollution
await Example.find();
const test = {};
console.log(test.polluted); // world!
console.log(Object.prototype); // [Object: null prototype] { polluted: 'world!' }
process.exit();
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mongoose
to version 5.13.20, 6.11.3, 7.3.4 or higher.
References
high severity
- Vulnerable module: url-parse
- Introduced through: amqplib@0.5.6
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › amqplib@0.5.6 › url-parse@1.4.7Remediation: Upgrade to amqplib@0.7.1.
Overview
url-parse is a Small footprint URL parser that works seamlessly across Node.js and browser environments.
Affected versions of this package are vulnerable to Improper Input Validation due to improper fix of CVE-2020-8124 , it is possible to be exploited via the \b
(backspace) character.
PoC:
const parse = require('./index.js')
url = parse('\bhttp://google.com')
console.log(url)
Output:
{
slashes: false,
protocol: '',
hash: '',
query: '',
pathname: '\bhttp://google.com',
auth: '',
host: '',
port: '',
hostname: '',
password: '',
username: '',
origin: 'null',
href: '\bhttp://google.com'
}
Remediation
Upgrade url-parse
to version 1.5.9 or higher.
References
high severity
- Vulnerable module: ammo
- Introduced through: hapi@16.8.4 and inert@4.2.1
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi@16.8.4 › ammo@2.1.2
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › inert@4.2.1 › ammo@2.1.2
Overview
ammo is a HTTP Range processing utilities.
Note This package is deprecated and is now maintained as @hapi/ammo
.
Affected versions of this package are vulnerable to Denial of Service (DoS). The Range HTTP header parser has a vulnerability which will cause the function to throw a system error if the header is set to an invalid value. Because hapi is not expecting the function to ever throw, the error is thrown all the way up the stack. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
There is no fixed version for ammo
.
References
high severity
- Vulnerable module: async
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › async@2.6.0Remediation: Upgrade to mongoose@5.7.3.
Overview
Affected versions of this package are vulnerable to Prototype Pollution via the mapValues()
method, due to improper check in createObjectIterator
function.
PoC
//when objects are parsed, all properties are created as own (the objects can come from outside sources (http requests/ file))
const hasOwn = JSON.parse('{"__proto__": {"isAdmin": true}}');
//does not have the property, because it's inside object's own "__proto__"
console.log(hasOwn.isAdmin);
async.mapValues(hasOwn, (val, key, cb) => cb(null, val), (error, result) => {
// after the method executes, hasOwn.__proto__ value (isAdmin: true) replaces the prototype of the newly created object, leading to potential exploits.
console.log(result.isAdmin);
});
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade async
to version 2.6.4, 3.2.2 or higher.
References
high severity
- Vulnerable module: hapi
- Introduced through: hapi@16.8.4
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi@16.8.4
Overview
hapi is a HTTP Server framework.
Affected versions of this package are vulnerable to Denial of Service (DoS). The CORS request handler has a vulnerability which will cause the function to throw a system error if the header contains some invalid values. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
There is no fixed version for hapi
.
References
high severity
- Vulnerable module: moment
- Introduced through: good-console@6.4.1
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › good-console@6.4.1 › moment@2.19.4Remediation: Upgrade to good-console@8.0.0.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Directory Traversal when a user provides a locale string which is directly used to switch moment locale.
Details
A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.
Directory Traversal vulnerabilities can be generally divided into two types:
- Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.
st
is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public
route.
If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.
curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa
Note %2e
is the URL encoded version of .
(dot).
- Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as
Zip-Slip
.
One way to achieve this is by using a malicious zip
archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.
The following is an example of a zip
archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/
overwriting the authorized_keys
file:
2018-04-15 22:04:29 ..... 19 19 good.txt
2018-04-15 22:04:42 ..... 20 20 ../../../../../../root/.ssh/authorized_keys
Remediation
Upgrade moment
to version 2.29.2 or higher.
References
high severity
- Vulnerable module: moment
- Introduced through: good-console@6.4.1
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › good-console@6.4.1 › moment@2.19.4Remediation: Upgrade to good-console@8.0.0.
Overview
moment is a lightweight JavaScript date library for parsing, validating, manipulating, and formatting dates.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the preprocessRFC2822()
function in from-string.js
, when processing a very long crafted string (over 10k characters).
PoC:
moment("(".repeat(500000))
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade moment
to version 2.29.4 or higher.
References
high severity
- Vulnerable module: mongodb
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › mongodb@2.2.34Remediation: Upgrade to mongoose@5.4.10.
Overview
mongodb is an official MongoDB driver for Node.js.
Affected versions of this package are vulnerable to Denial of Service (DoS). The package fails to properly catch an exception when a collection name is invalid and the DB does not exist, crashing the application.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade mongodb
to version 3.1.13 or higher.
References
high severity
- Vulnerable module: mquery
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › mquery@2.3.3Remediation: Upgrade to mongoose@5.12.3.
Overview
mquery is an Expressive query building for MongoDB
Affected versions of this package are vulnerable to Prototype Pollution via the mergeClone()
function.
PoC by zhou, peng
mquery = require('mquery');
var malicious_payload = '{"__proto__":{"polluted":"HACKED"}}';
console.log('Before:', {}.polluted); // undefined
mquery.utils.mergeClone({}, JSON.parse(malicious_payload));
console.log('After:', {}.polluted); // HACKED
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mquery
to version 3.2.5 or higher.
References
high severity
- Vulnerable module: subtext
- Introduced through: hapi@16.8.4
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi@16.8.4 › subtext@5.1.3
Overview
subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext
Affected versions of this package are vulnerable to Denial of Service (DoS).
The package fails to enforce the maxBytes
configuration for payloads with chunked encoding that are written to the file system. This allows attackers to send requests with arbitrary payload sizes, which may exhaust system resources.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.
Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.
One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.
When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.
Two common types of DoS vulnerabilities:
High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.
Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm
ws
package
Remediation
There is no fixed version for subtext
.
References
high severity
- Vulnerable module: subtext
- Introduced through: hapi@16.8.4
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi@16.8.4 › subtext@5.1.3
Overview
subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext
Affected versions of this package are vulnerable to Denial of Service (DoS). The Content-Encoding HTTP header parser has a vulnerability which will cause the function to throw a system error if the header contains some invalid values. Because hapi rethrows system errors (as opposed to catching expected application errors), the error is thrown all the way up the stack. If no unhandled exception handler is available, the application will exist, allowing an attacker to shut down services.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
There is no fixed version for subtext
.
References
high severity
- Vulnerable module: mquery
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › mquery@2.3.3Remediation: Upgrade to mongoose@5.11.7.
Overview
mquery is an Expressive query building for MongoDB
Affected versions of this package are vulnerable to Prototype Pollution via the merge
function within lib/utils.js
. Depending on if user input is provided, an attacker can overwrite and pollute the object prototype of a program.
PoC
require('./env').getCollection(function(err, collection) {
assert.ifError(err);
col = collection;
done();
});
var payload = JSON.parse('{"__proto__": {"polluted": "vulnerable"}}');
var m = mquery(payload);
console.log({}.polluted);
// The empty object {} will have a property called polluted which will print vulnerable
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mquery
to version 3.2.3 or higher.
References
high severity
- Vulnerable module: subtext
- Introduced through: hapi@16.8.4
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi@16.8.4 › subtext@5.1.3
Overview
subtext is a HTTP payload parsing library. Deprecated. Note: This package is deprecated and is now maintained as @hapi/subtext
Affected versions of this package are vulnerable to Prototype Pollution. A multipart payload can be constructed in a way that one of the parts’ content can be set as the entire payload object’s prototype. If this prototype contains data, it may bypass other validation rules which enforce access and privacy. If this prototype evaluates to null, it can cause unhandled exceptions when the request payload is accessed.
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
There is no fixed version for subtext
.
References
high severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21Remediation: Upgrade to mongoose@5.13.15.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Prototype Pollution in the Schema.path()
function.
Note: CVE-2022-24304 is a duplicate of CVE-2022-2564.
PoC:
const mongoose = require('mongoose');
const schema = new mongoose.Schema();
malicious_payload = '__proto__.toString'
schema.path(malicious_payload, [String])
x = {}
console.log(x.toString())
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mongoose
to version 5.13.15, 6.4.6 or higher.
References
medium severity
- Vulnerable module: jsonwebtoken
- Introduced through: hapi-auth-jwt2@7.4.1 and jsonwebtoken@7.4.3
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi-auth-jwt2@7.4.1 › jsonwebtoken@8.5.1Remediation: Upgrade to hapi-auth-jwt2@10.4.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › jsonwebtoken@7.4.3Remediation: Upgrade to jsonwebtoken@9.0.0.
Overview
jsonwebtoken is a JSON Web Token implementation (symmetric and asymmetric)
Affected versions of this package are vulnerable to Use of a Broken or Risky Cryptographic Algorithm such that the library can be misconfigured to use legacy, insecure key types for signature verification. For example, DSA keys could be used with the RS256 algorithm.
Exploitability
Users are affected when using an algorithm and a key type other than the combinations mentioned below:
EC: ES256, ES384, ES512
RSA: RS256, RS384, RS512, PS256, PS384, PS512
RSA-PSS: PS256, PS384, PS512
And for Elliptic Curve algorithms:
ES256: prime256v1
ES384: secp384r1
ES512: secp521r1
Workaround
Users who are unable to upgrade to the fixed version can use the allowInvalidAsymmetricKeyTypes
option to true
in the sign()
and verify()
functions to continue usage of invalid key type/algorithm combination in 9.0.0 for legacy compatibility.
Remediation
Upgrade jsonwebtoken
to version 9.0.0 or higher.
References
medium severity
- Vulnerable module: jsonwebtoken
- Introduced through: hapi-auth-jwt2@7.4.1 and jsonwebtoken@7.4.3
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi-auth-jwt2@7.4.1 › jsonwebtoken@8.5.1Remediation: Upgrade to hapi-auth-jwt2@10.4.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › jsonwebtoken@7.4.3Remediation: Upgrade to jsonwebtoken@9.0.0.
Overview
jsonwebtoken is a JSON Web Token implementation (symmetric and asymmetric)
Affected versions of this package are vulnerable to Improper Restriction of Security Token Assignment via the secretOrPublicKey
argument due to misconfigurations of the key retrieval function jwt.verify()
. Exploiting this vulnerability might result in incorrect verification of forged tokens when tokens signed with an asymmetric public key could be verified with a symmetric HS256 algorithm.
Note:
This vulnerability affects your application if it supports the usage of both symmetric and asymmetric keys in jwt.verify()
implementation with the same key retrieval function.
Remediation
Upgrade jsonwebtoken
to version 9.0.0 or higher.
References
medium severity
- Vulnerable module: jsonwebtoken
- Introduced through: hapi-auth-jwt2@7.4.1 and jsonwebtoken@7.4.3
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi-auth-jwt2@7.4.1 › jsonwebtoken@8.5.1Remediation: Upgrade to hapi-auth-jwt2@10.4.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › jsonwebtoken@7.4.3Remediation: Upgrade to jsonwebtoken@9.0.0.
Overview
jsonwebtoken is a JSON Web Token implementation (symmetric and asymmetric)
Affected versions of this package are vulnerable to Improper Authentication such that the lack of algorithm definition in the jwt.verify()
function can lead to signature validation bypass due to defaulting to the none
algorithm for signature verification.
Exploitability
Users are affected only if all of the following conditions are true for the jwt.verify()
function:
A token with no signature is received.
No algorithms are specified.
A falsy (e.g.,
null
,false
,undefined
) secret or key is passed.
Remediation
Upgrade jsonwebtoken
to version 9.0.0 or higher.
References
medium severity
- Vulnerable module: url-parse
- Introduced through: amqplib@0.5.6
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › amqplib@0.5.6 › url-parse@1.4.7Remediation: Upgrade to amqplib@0.7.1.
Overview
url-parse is a Small footprint URL parser that works seamlessly across Node.js and browser environments.
Affected versions of this package are vulnerable to Access Restriction Bypass due to improper parsing process, that may lead to incorrect handling of authentication credentials and hostname, which allows bypass of hostname validation.
PoC:
// PoC.js
var parse = require('url-parse')
var cc=parse("http://admin:password123@@127.0.0.1")
//Output:
{ slashes: true,
protocol: 'http:',
hash: '',
query: '',
pathname: '/',
auth: 'admin:password123',
host: '@127.0.0.1',
port: '',
hostname: '@127.0.0.1',
password: 'password123',
username: 'admin',
origin: 'http://@127.0.0.1',
href: 'http://admin:password123@@127.0.0.1/' }
Remediation
Upgrade url-parse
to version 1.5.6 or higher.
References
medium severity
- Vulnerable module: url-parse
- Introduced through: amqplib@0.5.6
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › amqplib@0.5.6 › url-parse@1.4.7Remediation: Upgrade to amqplib@0.7.1.
Overview
url-parse is a Small footprint URL parser that works seamlessly across Node.js and browser environments.
Affected versions of this package are vulnerable to Authorization Bypass via the hostname
field of a parsed URL, because "url-parse" is unable to find the correct hostname when no port number is provided in the URL.
PoC:
var Url = require('url-parse');
var PAYLOAD = "http://example.com:";
console.log(Url(PAYLOAD));
// Expected hostname: example.com
// Actual hostname by url-parse: example.com:
Output:
{
slashes: true,
protocol: 'http:',
hash: '',
query: '',
pathname: '/',
auth: '',
host: 'example.com:',
port: '',
hostname: 'example.com:',
password: '',
username: '',
origin: 'http://example.com:',
href: 'http://example.com:/'
}
Remediation
Upgrade url-parse
to version 1.5.8 or higher.
References
medium severity
- Vulnerable module: hoek
- Introduced through: good-sentry@1.0.3 and jsonwebtoken@7.4.3
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › good-sentry@1.0.3 › hoek@4.1.1Remediation: Upgrade to good-sentry@2.1.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › jsonwebtoken@7.4.3 › joi@6.10.1 › hoek@2.16.3Remediation: Upgrade to jsonwebtoken@8.0.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › jsonwebtoken@7.4.3 › joi@6.10.1 › topo@1.1.0 › hoek@2.16.3Remediation: Upgrade to jsonwebtoken@8.0.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › good-sentry@1.0.3 › hoek@4.1.1Remediation: Upgrade to good-sentry@2.1.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › jsonwebtoken@7.4.3 › joi@6.10.1 › hoek@2.16.3Remediation: Upgrade to jsonwebtoken@8.0.0.
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › jsonwebtoken@7.4.3 › joi@6.10.1 › topo@1.1.0 › hoek@2.16.3Remediation: Upgrade to jsonwebtoken@8.0.0.
Overview
hoek is an Utility methods for the hapi ecosystem.
Affected versions of this package are vulnerable to Prototype Pollution. The utilities function allow modification of the Object
prototype. If an attacker can control part of the structure passed to this function, they could add or modify an existing property.
PoC by Olivier Arteau (HoLyVieR)
var Hoek = require('hoek');
var malicious_payload = '{"__proto__":{"oops":"It works !"}}';
var a = {};
console.log("Before : " + a.oops);
Hoek.merge({}, JSON.parse(malicious_payload));
console.log("After : " + a.oops);
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade hoek
to version 4.2.1, 5.0.3 or higher.
References
medium severity
- Vulnerable module: url-parse
- Introduced through: amqplib@0.5.6
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › amqplib@0.5.6 › url-parse@1.4.7Remediation: Upgrade to amqplib@0.7.1.
Overview
url-parse is a Small footprint URL parser that works seamlessly across Node.js and browser environments.
Affected versions of this package are vulnerable to Authorization Bypass Through User-Controlled Key due to incorrect conversion of @
in the protocol field of the HREF.
PoC:
parse = require('url-parse')
console.log(parse("http:@/127.0.0.1"))
Output:
{
slashes: true,
protocol: 'http:',
hash: '',
query: '',
pathname: '/127.0.0.1',
auth: '',
host: '',
port: '',
hostname: '',
password: '',
username: '',
origin: 'null',
href: 'http:///127.0.0.1'
}
Remediation
Upgrade url-parse
to version 1.5.7 or higher.
References
medium severity
- Vulnerable module: mongoose
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21Remediation: Upgrade to mongoose@5.12.2.
Overview
mongoose is a Mongoose is a MongoDB object modeling tool designed to work in an asynchronous environment.
Affected versions of this package are vulnerable to Prototype Pollution. The mongoose.Schema()
function is subject to prototype pollution due to the recursively calling of Schema.prototype.add()
function to add new items into the schema object. This vulnerability allows modification of the Object prototype.
PoC
mongoose = require('mongoose');
mongoose.version; //'5.12.0'
var malicious_payload = '{"__proto__":{"polluted":"HACKED"}}';
console.log('Before:', {}.polluted); // undefined
mongoose.Schema(JSON.parse(malicious_payload));
console.log('After:', {}.polluted); // HACKED
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mongoose
to version 5.12.2 or higher.
References
medium severity
- Vulnerable module: mpath
- Introduced through: mongoose@4.13.21
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › mongoose@4.13.21 › mpath@0.5.1Remediation: Upgrade to mongoose@5.13.9.
Overview
mpath is a package that gets/sets javascript object values using MongoDB-like path notation.
Affected versions of this package are vulnerable to Prototype Pollution. A type confusion vulnerability can lead to a bypass of CVE-2018-16490. In particular, the condition ignoreProperties.indexOf(parts[i]) !== -1
returns -1
if parts[i]
is ['__proto__']
. This is because the method that has been called if the input is an array is Array.prototype.indexOf()
and not String.prototype.indexOf()
. They behave differently depending on the type of the input.
PoC
const mpath = require('mpath');
// mpath.set(['__proto__', 'polluted'], 'yes', {});
// console.log(polluted); // ReferenceError: polluted is not defined
mpath.set([['__proto__'], 'polluted'], 'yes', {});
console.log(polluted); // yes
Details
Prototype Pollution is a vulnerability affecting JavaScript. Prototype Pollution refers to the ability to inject properties into existing JavaScript language construct prototypes, such as objects. JavaScript allows all Object attributes to be altered, including their magical attributes such as __proto__
, constructor
and prototype
. An attacker manipulates these attributes to overwrite, or pollute, a JavaScript application object prototype of the base object by injecting other values. Properties on the Object.prototype
are then inherited by all the JavaScript objects through the prototype chain. When that happens, this leads to either denial of service by triggering JavaScript exceptions, or it tampers with the application source code to force the code path that the attacker injects, thereby leading to remote code execution.
There are two main ways in which the pollution of prototypes occurs:
Unsafe
Object
recursive mergeProperty definition by path
Unsafe Object recursive merge
The logic of a vulnerable recursive merge function follows the following high-level model:
merge (target, source)
foreach property of source
if property exists and is an object on both the target and the source
merge(target[property], source[property])
else
target[property] = source[property]
When the source object contains a property named __proto__
defined with Object.defineProperty()
, the condition that checks if the property exists and is an object on both the target and the source passes and the merge recurses with the target, being the prototype of Object
and the source of Object
as defined by the attacker. Properties are then copied on the Object
prototype.
Clone operations are a special sub-class of unsafe recursive merges, which occur when a recursive merge is conducted on an empty object: merge({},source)
.
lodash
and Hoek
are examples of libraries susceptible to recursive merge attacks.
Property definition by path
There are a few JavaScript libraries that use an API to define property values on an object based on a given path. The function that is generally affected contains this signature: theFunction(object, path, value)
If the attacker can control the value of “path”, they can set this value to __proto__.myValue
. myValue
is then assigned to the prototype of the class of the object.
Types of attacks
There are a few methods by which Prototype Pollution can be manipulated:
Type | Origin | Short description |
---|---|---|
Denial of service (DoS) | Client | This is the most likely attack. DoS occurs when Object holds generic functions that are implicitly called for various operations (for example, toString and valueOf ). The attacker pollutes Object.prototype.someattr and alters its state to an unexpected value such as Int or Object . In this case, the code fails and is likely to cause a denial of service. For example: if an attacker pollutes Object.prototype.toString by defining it as an integer, if the codebase at any point was reliant on someobject.toString() it would fail. |
Remote Code Execution | Client | Remote code execution is generally only possible in cases where the codebase evaluates a specific attribute of an object, and then executes that evaluation. For example: eval(someobject.someattr) . In this case, if the attacker pollutes Object.prototype.someattr they are likely to be able to leverage this in order to execute code. |
Property Injection | Client | The attacker pollutes properties that the codebase relies on for their informative value, including security properties such as cookies or tokens. For example: if a codebase checks privileges for someuser.isAdmin , then when the attacker pollutes Object.prototype.isAdmin and sets it to equal true , they can then achieve admin privileges. |
Affected environments
The following environments are susceptible to a Prototype Pollution attack:
Application server
Web server
Web browser
How to prevent
Freeze the prototype— use
Object.freeze (Object.prototype)
.Require schema validation of JSON input.
Avoid using unsafe recursive merge functions.
Consider using objects without prototypes (for example,
Object.create(null)
), breaking the prototype chain and preventing pollution.As a best practice use
Map
instead ofObject
.
For more information on this vulnerability type:
Arteau, Oliver. “JavaScript prototype pollution attack in NodeJS application.” GitHub, 26 May 2018
Remediation
Upgrade mpath
to version 0.8.4 or higher.
References
medium severity
- Vulnerable module: url-parse
- Introduced through: amqplib@0.5.6
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › amqplib@0.5.6 › url-parse@1.4.7Remediation: Upgrade to amqplib@0.7.1.
Overview
url-parse is a Small footprint URL parser that works seamlessly across Node.js and browser environments.
Affected versions of this package are vulnerable to Improper Input Validation. It mishandles certain uses of backslash such as http:\/
and interprets the URI as a relative path.
Remediation
Upgrade url-parse
to version 1.5.0 or higher.
References
medium severity
- Vulnerable module: url-parse
- Introduced through: amqplib@0.5.6
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › amqplib@0.5.6 › url-parse@1.4.7Remediation: Upgrade to amqplib@0.7.1.
Overview
url-parse is a Small footprint URL parser that works seamlessly across Node.js and browser environments.
Affected versions of this package are vulnerable to Open Redirect due to improper escaping of slash characters.
Remediation
Upgrade url-parse
to version 1.5.2 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: hapi-swagger@7.10.0
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi-swagger@7.10.0 › swagger-parser@3.4.2 › z-schema@3.25.1 › validator@10.11.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isSlug
function
PoC
var validator = require("validator")
function build_attack(n) {
var ret = "111"
for (var i = 0; i < n; i++) {
ret += "a"
}
return ret+"_";
}
for(var i = 1; i <= 50000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isSlug(attack_str)
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: hapi-swagger@7.10.0
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi-swagger@7.10.0 › swagger-parser@3.4.2 › z-schema@3.25.1 › validator@10.11.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isHSL
function.
PoC
var validator = require("validator")
function build_attack(n) {
var ret = "hsla(0"
for (var i = 0; i < n; i++) {
ret += " "
}
return ret+"◎";
}
for(var i = 1; i <= 50000; i++) {
if (i % 1000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isHSL(attack_str)
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.
References
medium severity
- Vulnerable module: validator
- Introduced through: hapi-swagger@7.10.0
Detailed paths
-
Introduced through: timelapse-api@j1348/timelapse-api#835cba42a49667ebe276a8a1f5e1d4f475135fa9 › hapi-swagger@7.10.0 › swagger-parser@3.4.2 › z-schema@3.25.1 › validator@10.11.0
Overview
validator is a library of string validators and sanitizers.
Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the isEmail
function.
PoC
var validator = require("validator")
function build_attack(n) {
var ret = ""
for (var i = 0; i < n; i++) {
ret += "<"
}
return ret+"";
}
for(var i = 1; i <= 50000; i++) {
if (i % 10000 == 0) {
var time = Date.now();
var attack_str = build_attack(i)
validator.isEmail(attack_str,{ allow_display_name: true })
var time_cost = Date.now() - time;
console.log("attack_str.length: " + attack_str.length + ": " + time_cost+" ms")
}
}
Details
Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.
The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.
Let’s take the following regular expression as an example:
regex = /A(B|C+)+D/
This regular expression accomplishes the following:
A
The string must start with the letter 'A'(B|C+)+
The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the+
matches one or more times). The+
at the end of this section states that we can look for one or more matches of this section.D
Finally, we ensure this section of the string ends with a 'D'
The expression would match inputs such as ABBD
, ABCCCCD
, ABCBCCCD
and ACCCCCD
It most cases, it doesn't take very long for a regex engine to find a match:
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total
$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total
The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.
Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.
Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:
- CCC
- CC+C
- C+CC
- C+C+C.
The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.
From there, the number of steps the engine must use to validate a string just continues to grow.
String | Number of C's | Number of steps |
---|---|---|
ACCCX | 3 | 38 |
ACCCCX | 4 | 71 |
ACCCCCX | 5 | 136 |
ACCCCCCCCCCCCCCX | 14 | 65,553 |
By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.
Remediation
Upgrade validator
to version 13.6.0 or higher.